[1]何争光,孙晓峰,马勇光..AdaBoost-NN模型在浊漳河水质评价中的应用[J].郑州大学学报(工学版),2007,28(01):114-117,121.[doi:10.3969/j.issn.1671-6833.2007.01.029]
 He Zhengguang,SUN Xiaofeng,Ma Yongguang.Application of AdaBoost-NN model in water quality evaluation of Zhuozhang River[J].Journal of Zhengzhou University (Engineering Science),2007,28(01):114-117,121.[doi:10.3969/j.issn.1671-6833.2007.01.029]
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AdaBoost-NN模型在浊漳河水质评价中的应用()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
28
期数:
2007年01期
页码:
114-117,121
栏目:
出版日期:
1900-01-01

文章信息/Info

Title:
Application of AdaBoost-NN model in water quality evaluation of Zhuozhang River
作者:
何争光孙晓峰马勇光.
郑州大学,环境与水利工程学院,河南,郑州,450001, 郑州大学,环境与水利工程学院,河南,郑州,450001, 郑州大学,环境与水利工程学院,河南,郑州,450001
Author(s):
He Zhengguang; SUN Xiaofeng; Ma Yongguang
关键词:
水质评价 BP网络 AdaBoost 泛化
Keywords:
DOI:
10.3969/j.issn.1671-6833.2007.01.029
文献标志码:
A
摘要:
为了克服传统BP网络的不足,将AdaBoost与神经网络结合,提出了基于AdaBoost-NN的水质评价模型.利用浊漳河水质监测数据比较AdaBoost-NN模型与传统ANN法和内梅罗综合指数法评价模型的差异,结果表明:AdaBoost-NN水质评价模型有效弥补了BP模型自身的缺陷,评价准确度更高,结果更加客观、合理.
Abstract:
In order to overcome the shortcomings of traditional BP networks, a water quality evaluation model based on AdaBoost-NN is proposed by combining AdaBoost with neural networks. The results show that the AdaBoost-NN water quality evaluation model effectively compensates for the shortcomings of the BP model, has higher evaluation accuracy, and the results are more objective and reasonable.

相似文献/References:

[1]贺北方,王效宇,贺晓菊,等.基于灰色聚类决策的水质评价方法[J].郑州大学学报(工学版),2002,23(01):10.[doi:10.3969/j.issn.1671-6833.2002.01.003]
 He Beibei,Wang Xiaoyu,HE Xiaoju,et al.Water quality evaluation method based on grey clustering decision[J].Journal of Zhengzhou University (Engineering Science),2002,23(01):10.[doi:10.3969/j.issn.1671-6833.2002.01.003]

更新日期/Last Update: 1900-01-01